Chromosome X plays a distinctive and notable role in human health and disease, but there is a fundamental gap in studying its function in complex human disease, because the vast majority of genome-wide association studies (GWAS) disregarded or incorrectly analyzed X-linked data. Hence, there is an urgent need for methods that will enable investigation of the X-linked basis of complex diseases, especially those that exhibit gender disparity in risk, age of onset, severity, o symptoms. Such methods must account for differences between chromosome X and the rest of the genome, including differences in the modes of inheritance, sexual dimorphism in susceptibility, dosage compensation (X-inactivation), population genetic patterns, and ascertainment biases. The overarching long-term goal of the research program is to improve the search for sex-linked complex disease genes and to elucidate how evolutionary history has shaped human genetic variation differently on the sex chromosomes. The objective of this application is to discover X-linked loci underlying various complex diseases while putting forth improved statistical and computational methods and software that are specially designed for chromosome X. The underlying rationale is that the proposed research will help uncover a portion of the heritable basis of complex disease that has yet to be explained by GWAS loci ('missing heritability'), reveal the role of chromosome X in disease etiology, and advance the exploration of the sex-linked basis of sex-specific disease patterns. Guided by extensive preliminary data and analysis, this objective will be met by pursuing three specific aims: (1) Develop new statistical and computational methodologies to facilitate powerful association studies that accommodate chromosome X;(2) Discover and replicate X-linked disease genes in existing and emerging GWAS datasets spanning different diseases and populations;(3) develop a software package for X-linked association studies. The innovation of the proposed research stems from the novel analytical methodologies that accurately deal with the challenges surrounding the analysis of chromosome X. Its contribution will be significant because it will bring chromosome X-which has so far been largely omitted-into the GWAS landscape and, specifically, will find novel X-linked associations underlying complex human disease while making analytical methods available for the next generation of association studies. This contribution will be further multiplied by offering a software package implementing all methods to the scientific community, thus allowing researchers to uncover X-linked genes underlying additional complex diseases and in additional populations. Collectively, the proposed research is significant as it will substantially advance our understanding of the role chromosome X plays in complex human disease.

Public Health Relevance

The proposed research is relevant to public health because it will leverage existing data to discover novel X-linked loci that are associated with inflated risk of complex disease, facilitate the unraveling of disease pathogenesis, and advance our understanding of the role sex chromosomes play in complex disease. Only after bridging this knowledge gap can substantial progress be made toward understanding the mechanisms underlying gender disparity in disease susceptibility. This project is relevant to the missions of NIH and NHGRI as it will advance human health by revealing genetic variants underlying complex human disease risk.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG006849-02
Application #
8731772
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Wise, Anastasia Leigh
Project Start
2013-09-09
Project End
2016-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Cornell University
Department
Biostatistics & Other Math Sci
Type
Earth Sciences/Resources
DUNS #
City
Ithaca
State
NY
Country
United States
Zip Code
14850
Waldman, Yedael Y; Biddanda, Arjun; Davidson, Natalie R et al. (2016) The Genetics of Bene Israel from India Reveals Both Substantial Jewish and Indian Ancestry. PLoS One 11:e0152056
D'Amico, Fabio; Skarmoutsou, Evangelia; Lo, Lauren J et al. (2016) Association between rs2294020 in X-linked CCDC22 and susceptibility to autoimmune diseases with focus on systemic lupus erythematosus. Immunol Lett 181:58-62
Slavney, Andrea; Arbiza, Leonardo; Clark, Andrew G et al. (2016) Strong Constraint on Human Genes Escaping X-Inactivation Is Modulated by their Expression Level and Breadth in Both Sexes. Mol Biol Evol 33:384-93
Billing-Ross, Paul; Germain, Arnaud; Ye, Kaixiong et al. (2016) Mitochondrial DNA variants correlate with symptoms in myalgic encephalomyelitis/chronic fatigue syndrome. J Transl Med 14:19
Gao, Feng; Keinan, Alon (2016) Inference of Super-exponential Human Population Growth via Efficient Computation of the Site Frequency Spectrum for Generalized Models. Genetics 202:235-45
Waldman, Yedael Y; Biddanda, Arjun; Dubrovsky, Maya et al. (2016) The genetic history of Cochin Jews from India. Hum Genet 135:1127-43
Gao, Feng; Keinan, Alon (2016) Explosive genetic evidence for explosive human population growth. Curr Opin Genet Dev 41:130-139
Pinto, Yishay; Gabay, Orshay; Arbiza, Leonardo et al. (2016) Clustered mutations in hominid genome evolution are consistent with APOBEC3G enzymatic activity. Genome Res 26:579-87
Blekhman, Ran; Goodrich, Julia K; Huang, Katherine et al. (2015) Host genetic variation impacts microbiome composition across human body sites. Genome Biol 16:191
Yu, Fuli; Lu, Jian; Liu, Xiaoming et al. (2015) Population genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions. PLoS One 10:e0121644

Showing the most recent 10 out of 23 publications